A survey of data-driven methods for materials modeling at nanoscale, mesoscale, and micro-to-continuum scales that identifies established capabilities, data quality issues, and obstacles to cross-scale integration.
Interpretable machine- learning strategy for soft-magnetic property and thermal stability in fe-based metal- lic glasses.npj Computational Materials, 6(1):187, 2020
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Materials Informatics Across the Length Scales
A survey of data-driven methods for materials modeling at nanoscale, mesoscale, and micro-to-continuum scales that identifies established capabilities, data quality issues, and obstacles to cross-scale integration.